• Journal of Applied Reliability
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• v.13 no.3
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• pp.175-190
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• 2013

This study considers reliability growth management as the excellent method for construction equipment development with the effect on decreasing COPQ(Cost of Poor Quality Cost) of new products. MIL-HDBK-189A(1981) and RADC-TR-84-20(1984) standards provide a general concept of reliability growth management including to reliability growth test, models and FRACAS(Failure Reporting and Corrective Action System). There is no study how to apply reliability growth management to construction equipment(or machine) development. This paper propose the method to apply it to construction equipment development process from the reliability target setting for developing products to launching them at market. It is expecially showing how to set target reliability for new developing equipment and the development risk to reach the reliability target in detail.

• Journal of Applied Reliability
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• v.5 no.3
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• pp.381-391
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• 2005

The level of reliability attained largely depends upon the investment in reliability growth programs during development phase. In order to find the relationship between reliability growth test time and BRTE(basic reliability tasks effectiveness) in a reliability improvement program that minimizes LCC in which contains the reliability growth cost, repair and replacement costs, and spare parts ordering costs in service with given service rate in management policy, the growth rate has been suggested proper LCC versus growth rate. This model employs the reliability growth projection with delayed fixes in avionic equipment based on AMSAA.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.90-100
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• 2015

Reliability growth rate (or reliability growth curve slope) have the two cases of trend as a constant or changing one during the reliability growth testing. The changing case is very common situation. The reasons of reliability growth rate changing are that the failures to follow the NHPP (None-Homogeneous Poisson Process), and the solutions implemented during test to break out other problems or not to take out all of the root cause permanently. If the changing were big, the "Goodness of Fit (GOF)" of reliability growth curve to test data would be very low and then reduce the accuracy of assessing result with test data. In this research, we are using Duane model and AMSAA model for assessing test data and projecting the reliability level of complex and repairable system as like construction equipment and vehicle. In case of no changing in reliability growth rate, it is reasonable for reliability engineer to implement the original Duane model (1964) and Crow-AMSAA model (1975) for the assessment and projection activity. However, in case of reliability growth rate changing, it is necessary to find the method to increase the "GOF" of reliability growth curves to test data. To increase GOF of reliability growth curves, it is necessary to find the proper parameter calculation method of interesting reliability growth models that are applicable to the situation of reliability growth rate changing. Since the Duane and AMSAA models have a characteristic to get more strong influence from the initial test (or failure) data than the latest one, the both models have a limitation to contain the latest test data information that is more important and better to assess test data in view of accuracy, especially when the reliability growth rate changing. The main objective of this research is to find the parameter calculation method to reflect the latest test data in the case of reliability growth rate changing. According to my experience in vehicle and construction equipment developments over 18 years, over the 90% in the total development cases are with such changing during the developing test. The objective of this research was to develop the newly assessing method and the process for GOF level increasing in case of reliability growth rate changing that would contribute to achieve more accurate assessing and projecting result. We also developed the new evaluation method for GOF that are applicable to the both models as Duane and AMSAA, so it is possible to compare it between models and check the effectiveness of new parameter calculation methods in any interesting situation. These research results can reduce the decision error for development process and business control with the accurately assessing and projecting result.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.187-198
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• 2019

Purpose: In this study, a reliability prediction based reliability growth management is suggested especially for the early development phase of a system and the case study of surveillance system is given. Methods: The proposed reliability prediction based reliability growth management procedures consists of 7 Steps. In Step 1, the stages for reliability growth management are classified according to the major design changes. From Step 2 to Step 5, system reliability is predicted based on reliability structures and the predicted reliabilities of subsystems (Level 2) and modules (Level 3). At each stage, by comparing the predicted system reliability with that of the previous stage, the reliability growth of the system is checked in Step 6. In Step 7, when the predicted value of sustem reliability does not satisfy the reliability goal, some design alternatives are considered and suggested to improve the system reliability. Results: The proposed reliability prediction based reliability growth management can be an efficient alternative for managing reliability growth of a system in its early development phase. The case study shows that it is applicable to weapon system such as a surveillance system. Conclusion: In this study, the procedures for a reliability prediction based reliability growth management are proposed to satisfy the reliability goal of the system efficiently. And it is expected that the use of the proposed procedures would reduce, in the test and evaluation phase, the number of corrective actions and its cost as well.

• Journal of Applied Reliability
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• v.13 no.3
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• pp.217-227
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• 2013

Reliability growth is defined as the positive improvement in a reliability parameter over a period of time due to implementation of corrective actions to system design, operation or maintenance procedures, or the associated manufacturing process. In recent, the importance of reliability growth management has emerged in the military authority and industries. For effective application of reliability growth models, it is necessary to understand their characteristics and differences. This paper presents the concepts of reliability growth management and compares the features of reliability tracking and projection models centered on MIL-HDBK-189C for selecting the appropriate model for an one-shot system under development.

• Journal of Applied Reliability
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• v.15 no.4
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• pp.248-255
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• 2015

Purpose : The purpose of this research is to develop the optimized method and process in the reliability-growth target setting, especially for complex and repairable system (or products) such as vehicle and airplane, construction equipment. Method : A reliability-growth test plan specifies a scenario to achieve the planned reliability value (or reliability target). The major elements in test planning are reliability-growth starting time and reliability level at that time, reliability-growth rate and reliability-growth target. All of them except a reliability target can be referred to the previous development data and reference researches. The reliability target level is directly influencing to test period (or time) which is related to test and warranty cost together. There are a few researches about the reliability target setting method and but showing the limitations to consider the views of engineering, business and customer together. There is no research how to handle the target setting process in detail. Result : We develop the optimized method and systematic process in reliability target setting with considering such views. This research also establish the new concept as production capability which means company (or supplier) capability to product its products. Conclusion : In this research result, we apply the new method to a few projects and can set the reasonable test planning. The developing results is showing the good balance between the developing cost and warranty cost at market.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.87-96
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• 2020

In this paper we proposed the test design method of reliability growth management. First, we presented the process for establishing the reliability growth management test design considering the number of failures and the termination test time. Reliability growth analysis of continuous system was performed in accordance with the test design process presented. In case the reliability test result is not met with the reliability target value after more than three failures occurred, the required test times were analyzed that 1,725 hrs for one corrective action, 1,950 hrs for two corrective actions. If the number of failures is less than three, design a reliability demonstration test according to confidence level 80% and 90% was performed using RGA 11 Software. As a result, it is possible to establish the reliability growth management test design with sufficient use of available resources. The results of this study can be used when establishing a test design for assessment of reliability growth management of all continuous systems.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.258-263
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• 2005

The purpose of this research is to present a practical method for efficiently monitoring a reliability growth process using AMSAA(Army Materiel Systems Analysis Activity) reliability growth model. The presented method is viable for identifying failure modes, incorporating design changes and monitoring reliability progress on an on-going basis during the early stages of a product development program. According to the Application Guide for EN 50126(RAM part for Rolling Stock), reliability growth monitoring is essential part of the main tasks of design phase in RAM growth monitoring. Implementation of reliability growth management program will provide very useful information on concept selection, product/process reliability, and cost effectiveness without too much time, money and engineering effort being spent on the development of failure suspect parts.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.981-994
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• 2017

Purpose: In this study, the reliability growth management procedures for armed vehicle is suggested and an illustrative case study of launcher system is given. Methods: Crow-AMSAA model is adopted to manage reliability growth of armed vehicle using failure data acquired from development test phase to field operation phase. Between the development test phase and the production phase, the suggested reliability growth procedures for armed vehicle entails accelerated life test of the selected module whose design is changed to improve its reliability for assuring the target system reliability. And it can be verified through estimating the system reliability based on the failure data of field operation phase. Results: It is shown that the proposed reliability growth management procedures are effective for armed vehicle based on the case study of launcher system. After estimating the reliability of launcher system at every development test, some items are selected to change their designs for improving reliability. Accelerated life test is performed to prove the reliability improvement and finally it is verified through the field operation. Conclusion: The reliability growth management procedures for armed vehicle is suggested and the case study of launcher system shows it can be effective for managing the reliability growth of the armed vehicle.